Systems and methods for traffic-flow regulation via centralized lateral flow control

A non-transitory computer-readable medium for traffic-flow regulation via centralized lateral flow control and storing instructions that, when executed by a processor, cause the processor to:

• receive aggregated macroscopic traffic state information from a section manager that communicates with one or more connected vehicles in a section of a roadway;
• process the aggregated macroscopic traffic state information using a reinforcement-learning-based model to determine target lateral flows for two or more lanes of the roadway in the section of the roadway;
• transmit the target lateral flows to the section manager, wherein the section manager converts the target lateral flows to lane-change actions and transmits the lane-change actions to the one or more connected vehicles;
• and
• control at least one of the one or more connected vehicles in performing a lane-change action, of the lane-change actions.

A method, comprising:

• receiving, at a locality manager that regulates traffic flow on a roadway via lateral flow control, aggregated macroscopic traffic state information from a section manager that communicates with one or more connected vehicles in a section of the roadway;
• processing the aggregated macroscopic traffic state information at the locality manager using a reinforcement-learning-based model to determine target lateral flows for two or more lanes of the roadway in the section of the roadway;
• transmitting the target lateral flows from the locality manager to the section manager, wherein the section manager converts the target lateral flows to lane-change actions and transmits the lane-change actions to the one or more connected vehicles;
• and
• controlling at least one of the one or more connected vehicles in performing a lane-change action, of the lane-change actions.